Constructing English-medium instruction indicators in the shipping courses of Taiwan's higher education. Issue 1 (19th March 2018) - Tseng, Po-Hsing; Richards, Kendall; Pilcher, Nick
Abstract : Purpose: This paper aims to use an analytic hierarchy process (AHP) and combine this with the fuzzy theory to identify key indicators influencing English-medium instruction (EMI) in the shipping courses of Taiwan's higher education. Design/methodology/approach: Based on a literature review and expert interviews, an evaluation model with 4 indicators and 13 sub-indicators was developed. Questionnaire samples included university English teachers (eight), university shipping teachers (nine) and shipping practitioners (eight). Findings: Using 25 effective samples, the results found that "teachers' characteristics" is the most important indicator, followed by "syllabus design", "university resources" and "students' characteristics". Such a finding could provide valuable teaching and managerial strategies for EMI design in both university and industry sectors. Research limitations/implications: Expert questionnaire targets have focused on university English teachers, university shipping teachers and shipping practitioners. Other related field experts could be further surveyed and compared in the future studies. Practical implications: The findings of EMI indicators in the shipping courses could be used for course and material design by shipping companies, shipping authorities and universities. It is expected that these indicators could inform the provision of reasonable teaching resources allocation. Social implications: This paper provides important guidance for designing EMI in shipping courses. Related stakeholders will be able to understand important concepts regarding designing EMI courses. Originality/value: First, EMI indicators in the shipping courses have seldom been studied in the past. They are, however, important for both shipping industries and education intuitions. Second, as its method, this paper adopts decision analysis quantitative tool to complement previous qualitative studies regarding EMI studies.